Evaluation of economics journals based on structural equation dimension reduction method

Abstract

Evaluation of economic journals is helpful to improve the quality of these journals. In this study, we adopt a new structural equation dimension reduction method to evaluate economics journals. We classify evaluation indexes based on cluster analysis and factor analysis to establish a structural equation model, normalize the regression coefficients to obtain the weight, and then weigh and summarize the first-level evaluation indexes for the ultimate dimension reduction and evaluation. The evaluation based on JCR 2019 Economics journals shows that the structural equation dimension reduction method overcomes the randomness of manual classification of evaluation indicators. The linear dimension reduction method is conducive to preserving a large amount of information of the original indicators; evaluating the first-level indicators facilitates the comprehensive evaluation of journals; the first-level indicators evaluation approach is more objective and reflects systematic academic evaluation. It should be noted that the stability of the structural equation has a significant impact on evaluation, which is generally suitable for a relatively mature academic evaluation.

Keywords

• economics
• evaluation index
• structural equation reduction method
• cluster analysis
• factor analysis